title: A dynamic network population model with strategic link formation governed by individual preferences.
abstract: Historically most evolutionary models have considered infinite populations with no structure. Recently more realistic evolutionary models have been developed using evolutionary graph theory, which considered the evolution of structured populations. The structures involved in these populations are typically fixed, however, and real populations change their structure over both long and short time periods. In this paper we consider the dynamics of such a population structure. The timescales involved are sufficiently short that no individuals are born or die, but the links between individuals are in a constant state of flux, being actively governed by the preferences of the members of the population. The process is modelled using a Markov chain over the possible structures. We find that under the specified process the population evolves to a closed class of structures, and we show a method to find the stationary distribution on this class. We also consider some special cases of interest.
authors.affiliation: Department of Mathematics, City University London, Northampton Square, London EC1V 0HB, UK. mark.broom@city.ac.uk
authors.forename: Mark
authors.initials: M
authors.lastname: Broom
authors.forename: Chris
authors.initials: C
authors.lastname: Cannings
mesh_terms: D000818:Animals; D008390:Markov Chains; D008954:Models, Biological; D011157:Population Dynamics
keywords: Degree-preferences; Graphic sequences; Markov process; Reversible process; Social networks